Magic Quadrant for AI-Augmented Software Testing Tools
Vendors or products added in this year’s report may indicate a change in the market, change in evaluation criteria, or change of focus by the vendor.
Vendors or products dropped from one year to the next may indicate a change in the market, change in evaluation criteria, or change of focus by the vendor.
No vendors were dropped in this report.
This is the first Magic Quadrant for AI-Augmented Software Testing Tools, replacing the previous Market Guide for AI-Augmented Software Testing Tools. By 2028, 70% of enterprises will have integrated AI-augmented software testing (AAST) tools into their software engineering toolchain, which is a significant increase from approximately 20% in early 2025. The market is experiencing rapid transformation with advances in agentic AI capabilities making testing processes increasingly autonomous. Vendors are pursuing a vision where numerous AI agents collaborate to perform tasks across design, coding, testing, deployment and monitoring stages without human intervention.
A: To qualify for inclusion in this Magic Quadrant, vendors needed to meet specific market participation criteria including: providing a dedicated, generally available AI-augmented software testing tool; having at least $30 million in annual GAAP revenue in 2024 with at least 200 paying enterprise customers, OR generating at least $25 million in annual GAAP revenue in 2024 with either 40% revenue growth YoY or 50 net-new enterprise logos added. Vendors also needed to meet technical capability requirements for mandatory features including conversational user interfaces, GenAI for test development, native automated UI/API/visual testing, self-healing, integrations, team collaboration, and enterprise administration. Additionally, vendors needed a Customer Interest Indicator (CII) score of at least 44. Vendors were excluded if their primary use case was testing low-code applications, packaged business applications, or SaaS-based applications, or if they targeted only a single system platform.